Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Group Discovery Time in Device-to-Device (D2D) Proximity Services (ProSe) Networks

Published

Author(s)

David W. Griffith, Aziza Ben Mosbah, Richard A. Rouil

Abstract

Device-to-device (D2D) communications for Long Term Evolution (LTE) networks relies on a discovery process to enable User Equipment (UE) to determine which D2D applications and services are supported by neighboring UEs. This is especially important for groups of UEs that operate outside the coverage area of any base station. The amount of time required for discovery information to reach every UE in a group depends on the number of UEs in the group and the dimensions of the discovery resource pool associated with the Physical Sidelink Discovery Channel (PSDCH); an additional factor is the half-duplex property of current UEs. In this paper, we use a Markov chain to characterize the performance of type~1 direct discovery in D2D networks. The resulting analytical model gives exact values for the distribution of the time for a UE to discover all other UEs in its group. We include a validation of the model using the NS3 network simulation tool. We use the model to measure the performance of D2D direct discovery as a function of D2D group size. We also examine the impact of the size and dimensions of the discovery resource pool.
Proceedings Title
IEEE INFOCOM 2017 - The 36th Annual IEEE International Conference on Computer Communications
Conference Dates
May 1-4, 2017
Conference Location
Atlanta, GA

Keywords

Device to Device, D2D, Discovery, Modeling, Markov chain

Citation

Griffith, D. , Ben, A. and Rouil, R. (2017), Group Discovery Time in Device-to-Device (D2D) Proximity Services (ProSe) Networks, IEEE INFOCOM 2017 - The 36th Annual IEEE International Conference on Computer Communications, Atlanta, GA, [online], https://doi.org/10.1109/INFOCOM.2017.8057077 (Accessed April 24, 2024)
Created May 3, 2017, Updated October 22, 2020